Currently, the most general application of 3D ultrasound imaging is to image a fetus in an obstetrical department, so that it can be observed clearly in clinic whether the fetus in a pregnant women's belly suffers from harelip, umbilical cord around neck etc. Additionally, the 3D ultrasound imaging can be used to observe gallbladder, bladder etc. The characteristics of such existing 3D imaging are that the imaged tissue motions rather slowly and the requirements as to time resolution are not high. In this case, the tissue to be imaged can be scanned using a common 1D probe driven by a free arm or a mechanical probe driven by a motor. The mechanical probe works generally at a speed of 2-4 frames per second. An advanced 3D ultrasound imaging, which targets at the organs which motion at higher speed such as heart, is mainly a 3D high-speed imaging using a 2D probe. Since the 2D probe is capable of obtaining data at a rather high speed, a relatively high time resolution can be reached, generally at 20 frames per second.
The 3D imaging process mainly includes data acquisition, data processing and imaging.
Data acquisition is a process of collecting volume data desired for 3D imaging. Taking a 1D probe driven by a free arm as an example, desired volume data are image sequences scanned by moving the 1D probe uniformly along the elevation direction of the probe. The volume data includes 3D information about the portion scanned by the probe, which is useful for 3D imaging. A mechanical probe is driven around a fulcrum by a motor, so that the desired volume data can be obtained in sector scanning way. A series of scanning line data are to be obtained in the data acquisition stage, which can also be considered as a series of image sequences before coordinate transformation. Each point in these data corresponds to a scanned point constituting the 3D object, which is referred to as a voxel.
Data processing is a process in which the acquired data is processed prior to imaging. It generally comprises data reconstruction, in which the collected polar coordinates are transformed into Cartesian coordinate. By said coordinate transformation, it is possible to obtain volume data in compliance with the real object, and the relative positions of the voxels are consistent with the real configuration.
Having been so processed, the volume data are then utilized for imaging. One of the most common imaging methods is the ray tracing method. Specifically, a viewpoint, a view plane and volume data are introduced into a virtual 3D space, and the volume data are re-sampled considering the line connecting the viewpoint to a pixel on the view plane as a ray direction. Finally, the re-sampled data are incorporated by a ray mathematical model to obtain a result that is the gray-scale value of the corresponding pixel on the view plane. When the gray-scale values for all pixels have been obtained, the imaging is finished.
The U.S. Pat. No. 5,911,691, assigned to Aloka, entitled “Ultrasound image processing apparatus and method of forming and displaying ultrasound images by the apparatus” describes a ray tracing method for 3D imaging in details.
As shown in FIG. 1, the above-mentioned patent suggests collecting data according to the position of a viewpoint. For a 1D mechanical probe, the radius for rotating the probe is identical to the radius of the probe, so that the obtained scanning line directions can extend to converge at the same point. Taking this point as the viewpoint, the ray direction coincides with the scanning line direction. That is to say, each of the scanning lines corresponds to a line that connects the viewpoint to a pixel on the view plane. Such a design significantly decreases the amount of calculation, because a) data reconstruction is no longer necessary; b) there is no need to calculate such parameters as an incident point etc. according to the ray direction or to perform a re-sampling operation.
With respect to imaging, the above-mentioned patent employs a conventional ray tracing method. The only difference is that imaging is realized by merely calculating each scanning line. As shown in FIG. 2, each cube represents a voxel in a ray (i.e. the scanning line in the U.S. Pat. No. 5,911,691); the parallelogram represents the view plane, that is, the resultant image. All data concerning a certain ray are synthesized to obtain a pixel P (x, y). An iterative process is used in data synthesis, which is a simulated process in which the ray passes through different mediums (attributes of the medium are described by values of a corresponding data point) and is absorbed. Each voxel has an opacity to correspond to a different gray-scale value, which is generally presented as a monotonic curve proportional to the gray-scale value. The opacity is denoted by ai and the gray-scale of the voxel is denoted by ei. Data synthesis is specified as follows:                i) For the first voxel, i=1, CINi=0;        ii) COUTi=(1−ai)*CINi+ai*eI;        iii) i=i+1, CINi=COUTi-1;        iv) if        
            ∑              k        =        1                    i        -        1              ⁢          a      i        =  1or i exceeds the range of the number of voxels, CINi is output; otherwise, skipping to ii).
The problem of the above-mentioned technical solution is that it relies on the probe in that the viewpoint, the rotary origin of the probe and the origin of the probe must coincide, which requires using a 2D probe or a particularly designed mechanical probe. This restricts the application of the technique. Moreover, once the viewpoint is fixed, such operations as magnifying and diminishing rotation cannot be carried out, because the operations will result in the ray deviating from the scanning line direction. Therefore, the above-described technical solution fails to decrease the amount of calculation, which is one of the important objects achieved by the present invention.